Report on the European working group on internal erosion, St. Petersburg
Bibliographic record
Abstract
This article reports on the seventh meeting of the working group, which was held on 27–29 April 2009 in St. Petersburg, hosted by VNIIG institute. There were 28 attendees from the UK, Canada, France, Sweden, Austria, Netherlands, Czech Republic and Poland and 12 attendees from Russia comprising, as in previous meetings, a mixture of researchers, practising engineers and dam safety managers. The workshop included 27 presentations and a visit to the hydraulic and soils laboratory of VNIIG. The participants included the authors of the current paper, which summarises the main points of relevance to dam engineers in the UK. The slide presentations are available on the VNIIG website http://www.vniig.ru/en/news/news25.htm . Selected summaries of work that had progressed since the intermediate report published at the European conference in Freising in September 2007 and presented in 2008 at Obergurgl in Austria and in 2009 at St. Petersburg are noted in the paper. VNIIG is a Russian research and development institute which carries out analysis and model testing in the fields of hydraulics, soil mechanics, concrete materials and safety of existing structures. One of its main clients is RusHydro, which was founded in 1921 and is the second largest generator in the world in terms of installed capacity, with 49 plants and 24 GW installed capacity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.026 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".